results-analysis

You can generate publication-ready regression tables by processing raw statistical output from Stata or Python. This Skill automates converting results into LaTeX tables that strictly adhere to social science journal standards for econometrics and political science publications.

Checking identification assumptions for DID, IV, and RDD designs is automated by this Skill. It validates pre-trends and other specific assumptions required for credible inference in social science research, ensuring your empirical strategy meets academic standards.

Yes, you can automatically draft the empirical results section of your research paper. This Skill interprets coefficient magnitudes, links findings back to theoretical frameworks, and generates narrative text suitable for social science publications directly from your regression output.

Creating event study, coefficient, and RD plots for causal inference designs is handled by this Skill. It transforms raw statistical output into publication-quality visualizations that clearly demonstrate pre-trends and treatment effects for social science research.

Yes, this tool fully supports Synthetic Control and RDD methodologies for data visualization. It produces publication-quality plots and performs identification checks specifically tailored to these advanced causal inference techniques alongside standard DID and IV designs.

You can analyze statistical output formats like Stata's smcl files or Python regression outputs. The Skill processes these raw empirical results to validate causal inference assumptions, generate LaTeX tables, and draft the corresponding econometrics results section text.